Sequential use of Geographic Information System and Mathematical

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Process Systems Engineering

Sequential use of Geographic Information System and Mathematical Programming for the Optimal planning for Energy Production System from Residual Biomass José Ezequiel Santibañez-Aguilar, Diego Fabián LozanoGarcia, Francisco Jose Lozano, and Antonio Flores-Tlacuahuac Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.9b00492 • Publication Date (Web): 16 May 2019 Downloaded from http://pubs.acs.org on May 16, 2019

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Industrial & Engineering Chemistry Research

Sequential use of Geographic Information System and Mathematical Programming for the Optimal planning for Energy Production System from Residual Biomass ∗

José E. Santibañez-Aguilar,

Diego F. Lozano-García, Francisco J. Lozano, and

Antonio Flores-Tlacuahuac

∗

School of Engineering and Science, Tecnologico de Monterrey, Monterrey, N.L., 64849, Mexico E-mail: [email protected]; antonio.[email protected] Phone: +52(1) 55 4347 2804

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Industrial & Engineering Chemistry Research 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Abstract Residual biomass is a renewable resource with attractive characteristics to produce energy and biofuels. Diverse studies have stated that residual biomass used for biofuels and energy production can contribute partially to solve the energy demand problem decreasing fossil fuels carbon emissions. Most works have focused on developing new technologies, processes and processing systems based on biomass. Other works have addressed the supply chain-planning problem to determine optimal locations considering diverse objectives. A third group of works have proposed schemes based on Geographic Information Systems (GIS) to determine suitable locations in dierent types of systems. Nevertheless, works capable to combine the advantage of GIS, mathematical programming and process design have not been properly conducted. Therefore, this paper presents a sequential approach for the optimal planning of a residual biomass processing system. The methodology considers selecting potential locations through a multi-criteria methodology based on GIS. Also, this paper proposes a mathematical programming approach for the optimal planning of a residual biomass processing system, which considers as input the locations pre-dened by GIS methodology as well as 6 potential products, 6 processing routes and 8 raw materials. The mathematical programming approach consists of mass balances to obtain the interconnections between the dierent supply chain nodes, as well as, constraints to model the considered technologies involving capital investment and production costs. GIS approach was applied to a case study in Mexico, which produced 764 harvesting sites and 334 processing plants for all considered residual biomass types. Optimization approach conducted to select 33 processing plants, 467 harvesting sites, and 2 of the products from 3 biomass types in order to determine the nal supply chain topology. Results show that the proposed methodology is a useful tool to determine the optimal supply chain topology during the making decision process.

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Introduction Facing the increasing

CO2

concentrations in the atmosphere, and its implications to climate

change, there is a need for humankind to address the issue and assess possible paths to mitigate the consequences or tread along a dierent development path. Based on dependence that our society has regarding fossil fuels, renewable sources such as biomass and its residues can be an attractive way to produce energy and chemicals, this idea has been addressed from 1945 or even before that. In fact, some US institutions during Second World War

proved

corn stover and wood for producing several chemicals such as sugars, ethanol, furfural, etc.

1

used corn stover to produce ethanol and furfural through hydrolysis and further fermentation. Also,

2

and

3

assessed the wood as raw material to obtain ethanol.

Regarding

4

alternatives for sustainable development and renewable energy production

have to be included in economic and social development in countries to avoid taking incorrect decisions in future years. Although, some enforces has gained importance in scientic community and society, presently humankind continues with high fossil fuels dependence; which perhaps continues in the near future. Some of enforces consist on carbon capture and sequestration, transition to a low carbon economy (

5

6

, ) and a generalized assessment of

renewable energy use. In this regard, biomass and its residues are some of the most important alternatives for a transition to a low carbon economy due to their important advantages regarding others. Some of the most important are: a)biomass exibility, b)reduction of overall greenhouse gas emissions (GHGE) and c)high biomass availability. Concerning the exibility, this is an important advantage since there are several types of biomass, which can be used to obtain a large portfolio of products including bio-fuels. In this regard,

7

reported a review for biofuels production through termochemical conversion. Also,

8

presented a making decision tool for the production of several products through dierent biomass types and processing routes in order to obtain the optimal prot and environmental impact.

3



According overall GHGE reduction

9

and

10

stated that fuels produced from biomass are

a good alternative to reduce the overall greenhouse gas emissions since biomass can capture a portion of emissions (produced due to its processing) during its growth. As mentioned, another biomass advantage is its high availability since most of countries have biomass production, which might be used as cattle, food, or raw material. To provide an idea about its availabilty, World Bioenergy Association

11

reported in 2012 that 37 % of

available land in the world was used to agricultural purposes whereas 30 % of available land in the world corresponded to forest area. Nevertheless, the biomass using is not developing in some emerging countries like Mexico. Even thoguh Mexico is one of the countries with major biodiversity. Regarding International Energy Agency

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biomass using for energetic purposes reached 6 % of total energy demand in

Mexico in 2014. In this context, it is critical to propose alternatives to promote the biomass using for dierent purposes (energy or chemicals) in order to address the global warming problem as well the energy and commodities production from renewable sources. Therefore this paper proposes a methodology based on geographic information system (GIS) using with mathematical programming to assess and design supply chains based on residual biomass in order to complement the transition towards a Low-Carbon Economy and consider biomass potential use as an energy generator, either electrical or thermal, as well as raw material for chemicals production, among which Fischer-Tropsch liquid fuels are an alternative. GIS and mathematical programming approaches are general and they can be applied to any case study. However, to prove the methodology we applied them for a case study in Mexico. The present paper is organized as follows: A discussion on

•

Residual biomass supply-chain planning

•

General background on potential uses for residual biomass

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•

Supply chain harvest sites location

•

Processing technologies and associated costs

•

Selection of technologies and locations and evaluation for each alternative for production

Followed on:

•

Problem Statement

•

Methodology (Based on GIS and Mathematical Programming)

•

Results and discussion

•

Conclusions and recommendations

Residual Biomass Supply chain planning Mexico has a large agricultural production, some crops can yield an adequate amount of residual biomass, such as corn stover, wheat and rice straw, sugar cane bagasse to mention a few. Table 1 presents the estimated residual biomass for some crops in 2014. Hence, an amount of nearly 50 million Mg/year has potential for further use. Furthermore, any supply chain can be dened as a set of facilities and processes involved into the production of valuable products from diverse raw materials, as well as the interactions between these facilities.

The facilities in general can be raw material suppli-

ers, processing plants, storage centers, retailers and consumers. In addition, a supply chain system can

be focused on chemicals production, as well as energy generation (electrical or

thermal). In the present paper the raw material is residual biomass that could be gasied with air or steam. Furthermore, the supply chain planning problem consists of determining the

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supply-chain topology (facility locations) as well as technologies, products and raw materials selection. It is worth noting that a supply chain topology has associated transportation costs between dierent considered locations and manufacturing costs related product production. These manufacturing costs depend over the processing technology. In this paper the basic chemical process for processing residual biomass is gasication, either with sub-stoichiometric air or with steam. The gasication renders a gas mixture which can be further processed as has been considered in.

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In order to generate a viable topology, harvesting sites location,

processing facilities location, available processing technologies and product distribution centers need to be determined. Furthermore sales and production costs are associated to each technology that allows the annual prot to be calculated. Table 1: Crop production and estimated residues generated in Mexico Year: 2014 Crop Name

Production (Mg/y)

Value (10

3

Mexican

Residue (Mg/y)

pesos) Agave

2,408,884

10,137,225

602,221

Palay rice

232,159

921,449

377,258

Sugarcane

56,672,829

26,225,927

7,650,832

Barley

845,707

2,950,771

1,403,874

23,133,599

72,077,147

19,085,219

122,536

6,106,022

224,853

3,971,536

12,644,957

7,287,768

95,781,306

151,049,709

48,593,556

Corn

(yellow

&

white) Pecan nut Wheat

(several

types) Grand total

General background on potential uses for residual biomass Using residual biomass as feedstock requires knowledge of available amounts, as well as its spatial distribution countrywide. Bioreneries where renewable raw materials are processed to yield various market chemicals are discussed by.

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Crops are harvested for human and

animal consumption, using them as raw material for energy purpose can distort the market by increasing prices, on the other hand residual biomass will not alter crop availability for

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food. Any country has specic regions for certain crops, Mexico's northern region produces pecan nut, while sorghum is produced mainly in the northeastern state of Tamaulipas,

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only

to mention two crops. In addition, harvesting occurs in specic municipalities within each state being this the data needed to pinpoint the spatial distribution. Hence, data gathering for residual biomass availability and distribution is one of the bases for the present paper. In order to estimate the residual biomass presented in Table 1, residue to crop ratio is given in Table 2. One main reason for using residual biomass is their neutrality towards greenhouse gas emissions. As compared to raw material production based on fossil fuels. Additionally, Table 2 provides values for agricultural reside price based on 10 % of average main crop value. It should be noticed that normally, these are residues without a signicant price respect to the main crop price.

Nevertheless, a residue price should be considered since if these are

used as raw material for a production system, the residues would gain economic value. Table 2: Residue to crop ratio and residue price Main crop

Agricultural

Residue amount

residue

per kg ( residue ) kgcrop

Agave

Agave residue

0.111

Rice

Rice straw

1.625

Sugar cane

Sugar

Barley

Barley straw

1.660

Maize

Maize stover

0.825

Pecan Nut

Pecan nut shell

0.550

Sorghum

Sorghum straw

1.425

Wheat

Wheat straw

1.835

cane

Reference

crop

residue

16 17 18

0.135

bagasse

Agricultural

19 17 17 17 17

price

($US/Mg)

10%

of

crop

main

(2014) 23.33 27.78 2.78 22.22 18.33 222.22 14.97 16.67

Not all residual biomass can be used for processing because from an agronomical standpoint a fraction has to be left in the harvesting place, as well as it is used for other purposes such as fodder.

According to

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biomass supply chains are strongly related to geographic

restrictions such as biomass availability or transportation infrastructure location. The latter implies that methods that take into account these considerations are needed in order

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to properly assess residual biomass potential uses.

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Moreover, Mexico has a large residual

biomass production, where harvesting sites are located in many states across the country. Relevant crops due to their large production, besides generating important residual biomass ows, are agave, corn, barley, sugar cane, sorghum, wheat, rice, and pecan nut. residual biomass estimation for the latter crops was in the order of 49x 10 agricultural food production was 235x10

6

Mg (

13

6

In 2014,

Mg; whereas,

).

As seen, supply chain planning is a complex problem, which should consider several aspects such as an adequate cost estimation for technologies, a multi-criteria strategy to determine facilities location and an optimization approach to get the best values for given objectives. This paper proposes a novel and robust strategy to determine the supply chain topology of a residual biomass processing system considering:

•

Manufacturing costs for each processing technology,

•

Facilities location facilities through a multi-criteria methodology based on GIS,

•

Mathematical formulation to determine supply chain topology maximizing annual prot.

Supply chain harvest sites location Crop biomass in Mexico is located within certain states, and in specic municipalities. Data for specic crops and their municipal production are available through the Federal Government Ministry of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA

15

). The relevance of this information is that it can be linked to a specic region

within any state, though not to a specic agricultural plot. Hence, residual biomass estimation can be calculated for each municipality and crop therein harvested; this provides raw material availability, as well as its spatial distribution in Mexico. For instance,

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carried out

the optimal planning of biomass processing, but they only considered 6 harvesting regions,

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5 consumption zones and 6 processing plants for a complete country.

In addition,

22

con-

sidered one processing facility for each state in Mexico for optimal planning of an integral agave utilization system. Also,

23

proposed the counties in Illinois as candidates for biomass

suppliers, new bioreneries and customers in Illinois for the optimal supply chain design considering uncertainty at dierent scales, but a specic location for supply chain facilities was not considered. Adding to modeling supply chain using biomass for power production

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discuss an optimization model in Italy using the net present value maximization for various technologies. As mentioned above, harvest sites location is a problem addressed previously, but many simplications have been done, therefore a robust and powerful tool that can be used to improve location are Geographic Information Systems (GIS), which address and manage geographic and spatial data, where specic restriction for decision making can be established. It should be noticed that location is a crucial variable because in some cases, energy used for transportation considering bad locations can be higher than the energy obtained from biomass (see

25

).

Moreover, it is worth noting that locations should also be viable loca-

tions. In consequence, this is an important opportunity for using GIS methods, since GIS approaches are capable to determine viable locations according to various criteria. Thus, several works have used GIS approaches to address the processing facility location problem, especially in biomass supply chains design.

For instance,

26

considered biomass

availability, transportation cost and raw material price into a system to use grasslands. In addition,

27

took into account the available biomass, price, and highways locations to produce

ethanol from grassland. Furthermore, a methodology to locate biomass suppliers considering exclusion of protected natural areas and soil erosion was presented by.

28

Additionally,

29

used

the distance between biomass suppliers and cities, as a decision parameter to locate entities in a production system based on residual biomass. Moreover,

30

developed an interesting method based on establishing a radius around biore-

neries to locate depots, where bioreneries were located in sites with high biomass availabil-

9



ity.

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presented a multi-objective scheme to select facilities from a sustainable point of view,

considering social and economic metrics, underlining the importance of social issues inclusion for site selection, as well as a methodology based on weighting accounted objectives, in the US Pacic Northwest region; though this study did not consider available biomass amount variability for bioreneries.

32

used an exclusion-inclusion approach to determine potential

locations in Georgia, USA for processing plants that use cotton stalks, and minimizing the delivery cost to obtain an optimal supply chain conguration, based on articial neural networks models; but the formulated model is not able to calculate plant capacities, though they consider that spatial and temporal variations aect the harvesting cost and other sustainability indicators. In addition,

33

presented a comprehensive biorenery approach to identify

important factors to be taken into account in bioethanol plants location using switchgrass, miscanthus and corn stover. Besides the work by,

32

previous articles have not considered the associated uncertainty

to the biomass availability as well as the risk related to biomass production.

Moreover,

most of studies have been applied to limited regions and not for a complete country. address these drawbacks,

34

To

developed a GIS approach to determine highly viable locations

of a biomass processing system considering several scenarios for the available biomass for Mexico. However,

34

only determined viable locations with high amount of available biomass

without any mathematical model for the supply chain optimization. Therefore, in current work we combine a GIS methodology to determine locations with high biomass availability and viability level with an optimization model in order to determine the optimal topology of a production system based on residual biomass for Mexico.

Processing Technologies and associated costs Biomass is an attractive source for fuels. Some of main advantages of biomass respect to conventional sources for fuels are: a) biomass can capture part of CO2 during its growth, b) biomass is a renewable source.

Also, biomass can be converted in dierent products

10


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(including fuels). One alternative for biomass processing is the biomass gasication that can be rst step for other processing routes. The main reaction paths considered follows:

•

Residual biomass gasication with sub-stoichiometric air (avoiding total combustion)

•

Residual biomass gasication with steam at high temperature.

The former renders a gas mixture containing carbon monoxide, hydrogen, methane, carbon dioxide and nitrogen as their main components; while the latter renders a gas mixture practically lacking nitrogen. The rst option can be used as fuel for a gas turbine, (generating electricity) whose exhaust gases are used to generate superheated high pressure steam (generating more electricity), and then the escape steam can be use in an absorption refrigeration system; this path provides electricity and thermal energy at two levels. Or can be used to generate Ammonia and Urea. The second option can be used to generate Methanol, Formaldehyde, Fischer-Tropsch liquids and Hydrogen for Fuel Cells. All these products have an important demand and high value in domestic and international market, since most of them can be used to produce other commodities. In this regard, an interesting alternative to produce these products is to use others sources such as residual biomass since biomass using could reduce the overall environmental impact provoked by the current process to obtain these products. It is worth noting that each technology could be economically evaluated; consequently, economic data are required, which depend on production capacity. These data can be obtained from technical reports, news, companies' websites, simulations under some assumptions, etc. This case, economic data for technologies such as capital investment or operating cost were taken from diverse sources; which are shown in Table 3. Economic data can be used to obtain a function for manufacturing cost for each considered technology. It is important to note that manufacturing cost including annualized capital investment, operating labor, supervision, maintenance, operating charges, overhead, property taxes, depreciation, administration costs, etc. An example for the functionality of manufacturing cost with production

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capacity is shown in Figure 1.

Figure 1: Representation of manufacturing cost from reported data for Methanol production

The manufacturing cost equation relating to production capacity is dened as:

M anuf Cost = M anuf Costref ·

CapP rod CapP rodref

m

Where:

M anuf Cost

Manufacturing Cost including Raw materials, Operating labor, Supervision, Maintenance, Operating charges, Overhead, Property taxes, Depreciation, Administration costs, etc.

CapP rod

Plant Production Capacity

M anuf Costref

Reference Manufacturing Cost

CapP rodref

Reference Production Capacity

m

Exponent, normally negative and

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Sequential use of Geographic Information System and Mathematical

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